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X Demographics
Mendeley readers
| Title |
Machine Learning Approaches Reveal That the Number of Tests Do Not Matter to the Prediction of Global Confirmed COVID-19 Cases
|
|---|---|
| Published in |
Frontiers in Artificial Intelligence, November 2020
|
| DOI | 10.3389/frai.2020.561801 |
| Pubmed ID | |
| Authors |
Hasinur Rahaman Khan, Ahmed Hossain |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 25% |
| Portugal | 1 | 25% |
| Switzerland | 1 | 25% |
| Unknown | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 50% |
| Members of the public | 2 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 32 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 5 | 16% |
| Researcher | 3 | 9% |
| Student > Doctoral Student | 3 | 9% |
| Lecturer | 2 | 6% |
| Student > Ph. D. Student | 2 | 6% |
| Other | 5 | 16% |
| Unknown | 12 | 38% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 5 | 16% |
| Medicine and Dentistry | 4 | 13% |
| Nursing and Health Professions | 3 | 9% |
| Agricultural and Biological Sciences | 2 | 6% |
| Psychology | 1 | 3% |
| Other | 3 | 9% |
| Unknown | 14 | 44% |